| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.179 | | leniency | 0.357 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1210 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 40.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 83.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1210 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "scanning" | | 1 | "weight" | | 2 | "aligned" | | 3 | "eyebrow" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 60 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 60 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1192 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 75.47% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 805 | | uniqueNames | 7 | | maxNameDensity | 1.49 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 12 | | Tube | 1 | | Camden | 1 | | Victorian-era | 1 | | Patel | 6 | | Chen | 2 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Camden" | | 2 | "Patel" | | 3 | "Chen" | | 4 | "Morris" |
| | places | | | globalScore | 0.755 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like charcoal: coordinates and a d" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.839 | | wordCount | 1192 | | matches | | 0 | "not from the entrance but from a recessed alcove" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 32.22 | | std | 24.24 | | cv | 0.752 | | sampleLengths | | 0 | 64 | | 1 | 13 | | 2 | 9 | | 3 | 57 | | 4 | 4 | | 5 | 38 | | 6 | 55 | | 7 | 1 | | 8 | 33 | | 9 | 60 | | 10 | 31 | | 11 | 14 | | 12 | 69 | | 13 | 5 | | 14 | 13 | | 15 | 44 | | 16 | 73 | | 17 | 17 | | 18 | 8 | | 19 | 41 | | 20 | 58 | | 21 | 5 | | 22 | 6 | | 23 | 46 | | 24 | 72 | | 25 | 10 | | 26 | 25 | | 27 | 16 | | 28 | 5 | | 29 | 52 | | 30 | 17 | | 31 | 53 | | 32 | 6 | | 33 | 82 | | 34 | 46 | | 35 | 5 | | 36 | 39 |
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| 81.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 60 | | matches | | 0 | "been poured" | | 1 | "been dragged" | | 2 | "was clenched" | | 3 | "was chosen" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 137 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 83 | | ratio | 0.108 | | matches | | 0 | "The smell hit Quinn first—copper and rot mingling with something acrid that made her sinuses burn." | | 1 | "Blood pooled beneath him, but the pattern was wrong—too contained, as if it had been poured rather than spilled from trauma." | | 2 | "She walked over, noting the scuff marks on the ground—circular patterns in the grime, as if something heavy had been dragged in circles." | | 3 | "Quinn catalogued each one—a discarded glass vial near marker three, scorch marks on the wall by marker seven, and near marker twelve, scratched into the brick in what looked like charcoal: coordinates and a date from two weeks prior." | | 4 | "She bent to examine it without touching, noting the residue coating the interior—dark and viscous, with an iridescent sheen when her light hit it at the right angle." | | 5 | "The body's position, the contained blood pool, the evidence of regular traffic, the coordinates, the vial—none of it aligned with a random vagrant attack." | | 6 | "She leaned closer, catching a scent beneath the blood—herbs and sulfur and something older, like church incense left to moulder in damp stone." | | 7 | "This location wasn't random—it was chosen, used, maintained by people who knew exactly what they were doing and went to lengths to keep it hidden." | | 8 | "Near the service tunnel entrance, another detail caught her attention—scratch marks in the concrete, forming what might have been symbols before time and wear had degraded them." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 817 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 27 | | adverbRatio | 0.033047735618115054 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0073439412484700125 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 14.36 | | std | 9.36 | | cv | 0.652 | | sampleLengths | | 0 | 16 | | 1 | 29 | | 2 | 19 | | 3 | 13 | | 4 | 9 | | 5 | 13 | | 6 | 23 | | 7 | 21 | | 8 | 4 | | 9 | 11 | | 10 | 27 | | 11 | 9 | | 12 | 9 | | 13 | 12 | | 14 | 15 | | 15 | 10 | | 16 | 1 | | 17 | 18 | | 18 | 15 | | 19 | 9 | | 20 | 16 | | 21 | 12 | | 22 | 23 | | 23 | 18 | | 24 | 13 | | 25 | 14 | | 26 | 10 | | 27 | 14 | | 28 | 8 | | 29 | 11 | | 30 | 12 | | 31 | 14 | | 32 | 5 | | 33 | 9 | | 34 | 4 | | 35 | 17 | | 36 | 27 | | 37 | 19 | | 38 | 15 | | 39 | 39 | | 40 | 6 | | 41 | 11 | | 42 | 8 | | 43 | 9 | | 44 | 12 | | 45 | 13 | | 46 | 7 | | 47 | 13 | | 48 | 28 | | 49 | 17 |
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| 85.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5180722891566265 | | totalSentences | 83 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 97.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 59 | | matches | | 0 | "She ducked beneath the police" | | 1 | "She'd seen claw marks before," | | 2 | "It led not from the" | | 3 | "She walked over, noting the" | | 4 | "She ran her light across" | | 5 | "She knelt, studying the threshold" | | 6 | "She pointed to a particularly" | | 7 | "She moved deeper into the" | | 8 | "She zoomed in on the" | | 9 | "She bent to examine it" | | 10 | "He'd been meeting someone, or" | | 11 | "Her gaze drifted to Chen's" | | 12 | "She moved back to the" | | 13 | "She leaned closer, catching a" | | 14 | "She pulled out her phone" | | 15 | "She photographed those too, already" | | 16 | "Her partner Morris had kept" | | 17 | "She'd avoided them since his" |
| | ratio | 0.305 | |
| 2.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 59 | | matches | | 0 | "The smell hit Quinn first—copper" | | 1 | "She ducked beneath the police" | | 2 | "The forensics lights cast harsh" | | 3 | "DS Patel waited at the" | | 4 | "Quinn snapped on the latex" | | 5 | "The body lay crumpled against" | | 6 | "Blood pooled beneath him, but" | | 7 | "Patel consulted his notebook" | | 8 | "Quinn crouched beside the body," | | 9 | "The edges were too clean" | | 10 | "She'd seen claw marks before," | | 11 | "These were similar but larger," | | 12 | "Patel shifted his weight" | | 13 | "Quinn stood, following the blood" | | 14 | "It led not from the" | | 15 | "The machines were long gone," | | 16 | "She walked over, noting the" | | 17 | "She ran her light across" | | 18 | "Quinn examined the chains that" | | 19 | "Someone had cut through weeks" |
| | ratio | 0.915 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 67.67% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 4 | | matches | | 0 | "She ducked beneath the police tape strung across the entrance to the abandoned Tube station, her boots finding purchase on the slick stairs that descended into …" | | 1 | "The body lay crumpled against the far wall, a young man in his twenties wearing an expensive jacket that didn't match the location." | | 2 | "This location wasn't random—it was chosen, used, maintained by people who knew exactly what they were doing and went to lengths to keep it hidden." | | 3 | "Her partner Morris had kept a network of specialists, academics who could identify obscure markings and unusual materials." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |